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  <div class="section" id="glossary">
<span id="id1"></span><h1>术语表<a class="headerlink" href="#glossary" title="Permalink to this headline">🔗</a></h1>
<dl class="glossary docutils">
<dt id="term-apache-hadoop">Apache Hadoop</dt>
<dd>See <a class="reference internal" href="#term-hadoop"><span class="xref std std-term">Hadoop</span></a>.</dd>
<dt id="term-apache-spark">Apache Spark</dt>
<dd>See <a class="reference internal" href="#term-spark"><span class="xref std std-term">Spark Program</span></a>.</dd>
<dt id="term-application">Application</dt>
<dd>A collection of programs and services that read and write through the data
abstraction layer in CDAP.</dd>
<dt id="term-application-abstraction">Application Abstraction</dt>
<dd>Application abstraction allows the same application to run in multiple environments
without modification.</dd>
<dt id="term-application-template">Application Template</dt>
<dd>An artifact, that with the addition of a configuration file, can be used to create
manifestations of applications.</dd>
<dt id="term-artifact">Artifact</dt>
<dd>A JAR file containing Java classes and resources required to create and run an
<a class="reference internal" href="#term-application"><span class="xref std std-term">Application</span></a>. Multiple applications can be created from the same artifact.</dd>
<dt id="term-avro">Avro</dt>
<dd>Refers to the <a class="reference external" href="http://avro.apache.org">Apache Avro™</a> project, which is a
data serialization system that provides rich data structures and a compact, fast, binary data format.</dd>
<dt id="term-batch-pipeline">Batch Pipeline</dt>
<dd>A type of <a class="reference internal" href="#term-cdap-pipeline"><span class="xref std std-term">CDAP Pipeline</span></a> that runs on a schedule, performing actions on
a distinct set of data.</dd>
<dt id="term-cdap">CDAP</dt>
<dd>The Cask Data Application Platform; refers to both the platform, and an installed instance of it.</dd>
<dt id="term-cdap-application">CDAP Application</dt>
<dd>See <a class="reference internal" href="#term-application"><span class="xref std std-term">Application</span></a>.</dd>
<dt id="term-cdap-cli">CDAP CLI</dt>
<dd>See <a class="reference internal" href="#term-command-line-interface"><span class="xref std std-term">Command Line Interface</span></a>.</dd>
<dt id="term-cdap-console">CDAP Console</dt>
<dd>See <a class="reference internal" href="#term-cdap-ui"><span class="xref std std-term">CDAP UI</span></a>.</dd>
<dt id="term-cdap-pipeline">CDAP Pipeline</dt>
<dd>A CDAP application; created from an application template, generally one
of the system artifacts shipped with CDAP; defines a source to read from, zero or more
transformations or other steps to perform on the data that was read from the source, and
one or more sinks to write the transformed data to.</dd>
<dt id="term-cdap-pipeline-plugin">CDAP Pipeline Plugin</dt>
<dd>A plugin of type BatchSource, RealtimeSource, BatchSink, RealtimeSink, or
Transformation, packaged in a JAR file format, for use as a plugin in a
CDAP pipeline.</dd>
<dt id="term-cdap-sandbox">CDAP Sandbox</dt>
<dd>A version of the Cask Data Application Platform, supplied as a downloadable archive,
that runs on a single machine in a single Java Virtual Machine (JVM). It provides
all of the CDAP APIs without requiring a Hadoop cluster, using alternative,
fully-functional implementations of CDAP features. For example, application
containers are implemented as Java threads instead of YARN containers. Formerly
known as the <a class="reference internal" href="#term-standalone-cdap"><span class="xref std std-term">Standalone CDAP</span></a>.</dd>
<dt id="term-cdap-studio">CDAP Studio</dt>
<dd>A visual editor, part of the <a class="reference internal" href="#term-cdap-ui"><span class="xref std std-term">CDAP UI</span></a>, for creating and configuring
pipelines. You click and drag sources, transformations, and sinks, and can name and
configure the pipelines. It provides an operational view of the resulting pipeline
that allows for monitoring of metrics, logs, and other run-time information.</dd>
<dt id="term-cdap-ui">CDAP UI</dt>
<dd>The CDAP UI is a web-based application used to deploy CDAP applications, create
<a class="reference internal" href="#term-48"><span class="xref std std-term">pipelines</span></a> using the <a class="reference internal" href="#term-cdap-studio"><span class="xref std std-term">CDAP Studio</span></a>, and query and
manage the Cask Data Application Platform instance.</dd>
<dt id="term-command-line-interface">Command Line Interface</dt>
<dd>The <a class="reference internal" href="cli-api.html#cli"><span class="std std-ref">Command Line Interface (CLI)</span></a> provides methods to interact with CDAP
from within a shell, similar to the HBase or <code class="docutils literal notranslate"><span class="pre">bash</span></code> shells.</dd>
<dt id="term-dag">DAG</dt>
<dd>A directed acyclic graph. A Pipeline is displayed as a DAG in the CDAP UI.</dd>
<dt id="term-data-abstraction">Data Abstraction</dt>
<dd>Abstraction of the actual representation of data in storage.</dd>
<dt id="term-data-pipeline">Data Pipeline</dt>
<dd>A type of <a class="reference internal" href="#term-48"><span class="xref std std-term">pipeline</span></a>, often not linear in nature and require the performing of
complex transformations including forks and joins at the record and feed level. They
can be configured to perform various functions at different times, including
machine-learning algorithms and custom processing.</dd>
<dt id="term-dataset">Dataset</dt>
<dd>Datasets store and retrieve data and are a high-level abstraction of the underlying
data storage with generic reusable implementations of common data patterns.</dd>
<dt id="term-distributed-cdap">Distributed CDAP</dt>
<dd>A version of the Cask Data Application Platform, supplied as either Yum <code class="docutils literal notranslate"><span class="pre">.rpm</span></code> or
APT <code class="docutils literal notranslate"><span class="pre">.deb</span></code> packages, that runs on a <a class="reference internal" href="#term-hadoop"><span class="xref std std-term">Hadoop</span></a> cluster. Packages are available
for <em>Ubuntu 12</em> and <em>CentOS 6</em>.</dd>
<dt id="term-etl">ETL</dt>
<dd>Abbreviation for <em>extract,</em> <em>transform,</em> and <em>loading</em> of data.</dd>
<dt id="term-38">ETL</dt>
<dd>Refers to the <em>Extract</em>, <em>Transform</em> and <em>Load</em> of data.</dd>
<dt id="term-exploring">Exploring</dt>
<dd>Datasets in CDAP can be explored through ad-hoc SQL-like queries. To
enable exploration, you must set several properties when creating the
dataset, and the files in a dataset must meet certain requirements.</dd>
<dt id="term-fileset">FileSet</dt>
<dd>A <a class="reference internal" href="#term-dataset"><span class="xref std std-term">dataset</span></a> composed of collections of files in the file system that share
some common attributes such as the format and schema, which abstracts from the
actual underlying file system interfaces.</dd>
<dt id="term-hadoop">Hadoop</dt>
<dd><p class="first">Refers to the <a class="reference external" href="http://hadoop.apache.org">Apache Hadoop®</a> project, which describes
itself as:</p>
<p class="last"><em>“The Apache Hadoop software library is a framework that allows for the distributed
processing of large data sets across clusters of computers using simple programming
models. It is designed to scale up from single servers to thousands of machines,
each offering local computation and storage. Rather than rely on hardware to deliver
high-availability, the library itself is designed to detect and handle failures at
the application layer, so delivering a highly-available service on top of a cluster
of computers, each of which may be prone to failures.”</em></p>
</dd>
<dt id="term-logical-pipeline">Logical Pipeline</dt>
<dd>A view of a <a class="reference internal" href="#term-48"><span class="xref std std-term">pipeline</span></a> composed of sources, sinks, and other plugins, and does
not show the underlying technology used to actually manifest and run the pipeline.</dd>
<dt id="term-mapreduce">MapReduce</dt>
<dd>MapReduce is a processing model used to process data in batch. MapReduce programs can be
written as in a conventional Apache Hadoop system. CDAP datasets can be accessed
from MapReduce programs as both input and output.</dd>
<dt id="term-master-services">Master Services</dt>
<dd>CDAP system services that are run in YARN containers, such as the Transaction Service,
Dataset Executor, Log Saver, Metrics Processor, etc.</dd>
<dt id="term-namespace">Namespace</dt>
<dd>A namespace is a logical grouping of application, data and its metadata in CDAP.
Conceptually, namespaces can be thought of as a partitioning of a CDAP instance. Any
application or data (referred to here as an “entity”) can exist independently in
multiple namespaces at the same time. The data and metadata of an entity is stored
independent of another instance of the same entity in a different namespace. The
primary motivation for namespaces in CDAP is to achieve application and data
isolation.</dd>
<dt id="term-physical-pipeline">Physical Pipeline</dt>
<dd>A physical pipeline is the manifestation of a <a class="reference internal" href="#term-logical-pipeline"><span class="xref std std-term">logical pipeline</span></a> as a CDAP
application, which is a collection of programs and services that read and write
through the data abstraction layer in CDAP.</dd>
<dt id="term-pipeline">Pipeline</dt>
<dd>CDAP provides an easy method of configuring
pipelines using a visual editor, called <a class="reference internal" href="#term-cdap-studio"><span class="xref std std-term">CDAP Studio</span></a>. You click and
drag sources, transformations, and sinks, configuring an pipeline within minutes. It
provides an operational view of the resulting pipeline that allows for monitoring of
metrics, logs, and other run-time information.</dd>
<dt id="term-48">Pipeline</dt>
<dd>A pipeline is a series of stages—linked usages of individual programs—configured together into an application.</dd>
<dt id="term-plugin">Plugin</dt>
<dd>A plugin extends an <a class="reference internal" href="#term-application"><span class="xref std std-term">application</span></a> by implementing an interface
expected by the <a class="reference internal" href="#term-application"><span class="xref std std-term">application</span></a>. Plugins are packaged in an <a class="reference internal" href="#term-artifact"><span class="xref std std-term">artifact</span></a>.</dd>
<dt id="term-49">Plugin</dt>
<dd>A plugin extends an application template by implementing an interface expected by
the application template. Plugins are packaged in an artifact.</dd>
<dt id="term-real-time-pipeline">Real-time Pipeline</dt>
<dd>A type of <a class="reference internal" href="#term-cdap-pipeline"><span class="xref std std-term">CDAP Pipeline</span></a> that runs continuously, performing actions on
a distinct set of data.</dd>
<dt id="term-route-config">Route Config</dt>
<dd>See <a class="reference internal" href="#term-route-configuration"><span class="xref std std-term">route configuration</span></a>.</dd>
<dt id="term-route-configuration">Route Configuration</dt>
<dd>Also known as a <em>route config</em>, a map that allocates requests for a service between
different versions of the service.</dd>
<dt id="term-secure-key">Secure Key</dt>
<dd>An identifier or an alias for an entry in <a class="reference internal" href="#term-secure-storage"><span class="xref std std-term">Secure Storage</span></a>. An entry in secure
storage can be referenced and retrieved using a Secure Key using <a class="reference external" href="../../developer-manual/building-blocks/secure-keys.html#secure-keys-programmatic" title="(in Cask Data Application Platform v6.1.1)"><span class="xref std std-ref">programmatic</span></a>
or <a class="reference internal" href="http-restful-api/security.html#http-restful-api-secure-storage"><span class="std std-ref">RESTful</span></a> APIs.</dd>
<dt id="term-secure-storage">Secure Storage</dt>
<dd>Encrypted storage for sensitive data using <a class="reference internal" href="#term-secure-key"><span class="xref std std-term">Secure Keys</span></a>. CDAP supports <a class="reference external" href="../../admin-manual/security/secure-storage.html#admin-secure-storage-file" title="(in Cask Data Application Platform v6.1.1)"><span class="xref std std-ref">File-backed</span></a> (for <a class="reference internal" href="#term-cdap-sandbox"><span class="xref std std-term">CDAP Sandbox</span></a>) as well as <a class="reference external" href="../../admin-manual/security/secure-storage.html#admin-secure-storage-kms" title="(in Cask Data Application Platform v6.1.1)"><span class="xref std std-ref">Apache Hadoop KMS-backed</span></a> (for <a class="reference internal" href="#term-distributed-cdap"><span class="xref std std-term">Distributed CDAP</span></a>) Secure Storage.</dd>
<dt id="term-service">Service</dt>
<dd>Services can be run in a Cask Data Application Platform (CDAP) application to serve
data to external clients. Services run in containers and the
number of running service instances can be dynamically scaled. Developers can
implement custom services to interface with a legacy system and perform additional
processing beyond the CDAP processing paradigms. Examples could include running an
IP-to-Geo lookup and serving user-profiles.</dd>
<dt id="term-spark">Spark</dt>
<dd>Spark is a fast and general processing engine, compatible with Hadoop data, used for
in-memory cluster computing. It lets you load large sets of data into memory and
query them repeatedly, making it suitable for both iterative and interactive
programs. Similar to <a class="reference internal" href="#term-mapreduce"><span class="xref std std-term">MapReduce</span></a>, Spark can access datasets as both input and output.
Spark programs in CDAP can be written in either Java or Scala.</dd>
<dt id="term-standalone-cdap">Standalone CDAP</dt>
<dd>See <a class="reference internal" href="#term-cdap-sandbox"><span class="xref std std-term">CDAP Sandbox</span></a>.</dd>
<dt id="term-storage-provider">Storage Provider</dt>
<dd>For <a class="reference internal" href="#term-dataset"><span class="xref std std-term">datasets</span></a>, a storage provider is the underlying
system that CDAP uses for persistence. Examples include HDFS, HBase, and Hive.</dd>
<dt id="term-structured-record">Structured Record</dt>
<dd>The data format used to exchange events between most of the pre-built CDAP ETL <a class="reference internal" href="#term-49"><span class="xref std std-term">plugins</span></a>.</dd>
<dt id="term-51">Structured Record</dt>
<dd>A data format, defined in CDAP, that can be used to exchange events
between plugins. Used by many of the <a class="reference internal" href="#term-cdap-pipeline-plugin"><span class="xref std std-term">CDAP pipeline plugins</span></a> included in CDAP.</dd>
<dt id="term-system-artifact">System Artifact</dt>
<dd>An application template, shipped with CDAP, that with the addition of a
configuration file, can be used to create manifestations of applications.</dd>
<dt id="term-time-partitioned-fileset">Time-partitioned FileSet</dt>
<dd>A <a class="reference internal" href="#term-fileset"><span class="xref std std-term">FileSet</span></a> <a class="reference internal" href="#term-dataset"><span class="xref std std-term">dataset</span></a> that uses a timestamp as the partitioning key to
split the data into indivividual files. Though it is not required that data in each
partition be organized by time, each partition is assigned a logical time. Typically
written to in batch mode, at a set time interval.</dd>
<dt id="term-timeseries-dataset">Timeseries Dataset</dt>
<dd>A <a class="reference internal" href="#term-dataset"><span class="xref std std-term">dataset</span></a> where time is the primary means of how data is organized, and both
the data model and the schema that represents the data are optimized for querying
and aggregating over time ranges.</dd>
<dt id="term-worker">Worker</dt>
<dd>Workers are typically long-running background programs that can be used to execute tasks.
Each instance of a worker runs either in its own YARN container (Distributed CDAP mode) or
a single thread (CDAP Sandbox or in-memory mode) and the number of instances may be updated
via RESTful APIs or the CLI. Datasets can be accessed from inside workers.</dd>
<dt id="term-workflow">Workflow</dt>
<dd>A workflow is used to execute a series of MapReduce programs, with an optional schedule
to run itself periodically.</dd>
</dl>
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